Applied Statistical Methods in Agriculture, Health and Life, 

Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman
Название: The Elements of Statistical Learning
ISBN: 0387848576 ISBN-13(EAN): 9780387848570
Издательство: Springer
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Цена: 69870.00 T
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Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.

Автор: Malley
Название: Statistical Learning for Biomedical Data
ISBN: 0521699096 ISBN-13(EAN): 9780521699099
Издательство: Cambridge Academ
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Цена: 43290.00 T
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Описание: Biomedical researchers need machine learning techniques to make predictions such as survival/death or response to treatment when data sets are large and complex. This highly motivating introduction to these machines explains underlying principles in nontechnical language, using many examples and figures, and connects these new methods to familiar techniques.

Автор: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
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Цена: 60190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

Автор: Agarwal
Название: Statistical Methods for Recommender Systems
ISBN: 1107036070 ISBN-13(EAN): 9781107036079
Издательство: Cambridge Academ
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Цена: 50680.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Designing algorithms to recommend items such as news articles and movies to users is a challenging task in numerous web applications. The crux of the problem is to rank items based on users' responses to different items to optimize for multiple objectives. Major technical challenges are high dimensional prediction with sparse data and constructing high dimensional sequential designs to collect data for user modeling and system design. This comprehensive treatment of the statistical issues that arise in recommender systems includes detailed, in-depth discussions of current state-of-the-art methods such as adaptive sequential designs (multi-armed bandit methods), bilinear random-effects models (matrix factorization) and scalable model fitting using modern computing paradigms like MapReduce. The authors draw upon their vast experience working with such large-scale systems at Yahoo! and LinkedIn, and bridge the gap between theory and practice by illustrating complex concepts with examples from applications they are directly involved with.

Автор: Becketti
Название: Introduction to Time Series Using Stata
ISBN: 1597181323 ISBN-13(EAN): 9781597181327
Издательство: Taylor&Francis
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Цена: 75530.00 T
Наличие на складе: Невозможна поставка.
Описание: Recent decades have witnessed explosive growth in new and powerful tools for timeseries analysis. These innovations have overturned older approaches to forecasting, macroeconomic policy analysis, the study of productivity and long-run economic growth, and the trading of financial assets. Familiarity with these new tools on time series is an essential skill for statisticians, econometricians, and applied researchers. Introduction to Time Series Using Stata provides a step-by-step guide to essential timeseries techniques—from the incredibly simple to the quite complex—and, at the same time, demonstrates how these techniques can be applied in the Stata statistical package. The emphasis is on an understanding of the intuition underlying theoretical innovations and an ability to apply them. Real-world examples illustrate the application of each concept as it is introduced, and care is taken to highlight the pitfalls, as well as the power, of each new tool. Sean Becketti is a financial industry veteran with three decades of experience in academics, government, and private industry. Over the last two decades, Becketti has led proprietary research teams at several leading financial firms, responsible for the models underlying the valuation, hedging, and relative value analysis of some of the largest fixed-income portfolios in the world.

Автор: Heeringa
Название: Applied Survey Data Analysis, Second Edition
ISBN: 1498761607 ISBN-13(EAN): 9781498761604
Издательство: Taylor&Francis
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Цена: 91860.00 T
Наличие на складе: Нет в наличии.
Описание: This book provides an overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more examples the analysis of survey data.

Автор: James Gareth
Название: An Introduction to Statistical Learning
ISBN: 1461471370 ISBN-13(EAN): 9781461471370
Издательство: Springer
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Цена: 60550.00 T
Наличие на складе: Невозможна поставка.
Описание: This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.

Автор: J. Philip Miller
Название: Essential Statistical Methods for Medical Statistics,
ISBN: 0444537376 ISBN-13(EAN): 9780444537379
Издательство: Elsevier Science
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Цена: 56940.00 T
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Описание: Addresses statistical challenges in epidemiological, biomedical, and pharmaceutical research. This book presents methods for assessing Biomarkers, analysis of competing risks. It offers clinical trials including sequential and group sequential, crossover designs, cluster randomized, and adaptive designs.

Автор: Bethlehem
Название: Applied Survey Methods - A Statistical Perspective
ISBN: 0470373083 ISBN-13(EAN): 9780470373088
Издательство: Wiley
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Цена: 130890.00 T
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Описание: Emphasizing the statistical aspects of survey methods, Applied Survey Methods describes the complete survey process, from design to publication. This valuable book provides an overview of the theory as well as the practical applications of survey research methods, such as item and unit non-response and the associated treatment.

Автор: Hang Lee
Название: Foundations of Applied Statistical Methods
ISBN: 3319347241 ISBN-13(EAN): 9783319347240
Издательство: Springer
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Цена: 46570.00 T
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Описание: Driven by real-world examples, this book covers applied statistical methods in a concise and easily accessible way. Coverage includes essential probability models, inference of means, proportions, correlations and regressions, and sample size determination.

Автор: Peter Sprent
Название: Applied Nonparametric Statistical Methods
ISBN: 940107044X ISBN-13(EAN): 9789401070447
Издательство: Springer
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Цена: 81050.00 T
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Описание: Understanding the rudiments helps one get better performance and makesdrivingsafer;appropriate gearchanges become a way to reduce engine stress, prolong engine life, improve fuel economy, minimize wear on brake linings.

Автор: Bayo Lawal
Название: Applied Statistical Methods in Agriculture, Health and Life Sciences
ISBN: 3319378341 ISBN-13(EAN): 9783319378343
Издательство: Springer
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Цена: 69870.00 T
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Описание: This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. It is developed for undergraduate students in agriculture, nursing, biology and biomedical research.